AI engineering glossary · Probability
What is chebyshev's inequality?
Chebyshev's inequality: A guarantee that for any distribution with a finite mean and variance, the probability that a value lies more than k standard deviations from the mean is at most 1 / k^2. It gives bounds without assuming a bell shape.
Chebyshev's inequality: an example
At most 1/4 = 25% of values can lie more than 2 standard deviations from the mean, whatever the distribution.
Related terms
More Probability terms
- Classical probability
- Cluster sampling
- Combination
- Complement rule
- Conditional distribution
- Conditional expectation
- Conditional probability
- Confounding variable
Where you learn it
Chebyshev's inequality is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.